On the adaption of data mining technology to categorize cancer diseases

Abstract

Along with data mining, tools and software have emerged to aid in mining the vast and growing amount of data to access knowledge in databases. These tools facilitate work on most scientific disciplines, including sciences, Libraries and information. Accordingly, Data mining became an effective technique for obtaining knowledge to achieve the basic goal of discovering hidden facts that are contained in databases through the use of multiple technologies that include artificial intelligence, statistical analyzes, techniques and data modeling etc. Medical data mining is considered one of the most important tools used in the field of medicine, especially in exploring and knowing health conditions according to records of former patients. In addition, data mining helps not only in categorizing cancer but also in taking the necessary measures. With the spread of cancer at high rates around the world, the need to develop smart methods that have the ability to predict the disease appeared. Applications of data mining techniques spread as human attempts to control this deadly disease, with the aim of awareness, early detection and reduction of treatment costs. This prompted the researcher's curiosity to know the ability of data mining to categorize cancer. This work aims at reviewing ways to solve one of the problems that doctors suffer from, which is the problem of diagnosing diseases that lead to death, including cancer, as there is huge information that has not been used. Therefore, this work tries to solve this problem using data mining technology in addition to helping doctors make the right decision. The study reached several conclusions, namely the fact that the studies presented in the paper demonstrated the effective role of data mining techniques in reducing medical errors in terms of their ability to predict and accurately diagnose the disease, as well as the effectiveness of the algorithms of the data mining technique in predicting the presence of the disease at an early stage. Thus, we found that the clinical field needs to expand research, foster new kinds of calculations, and apply them practically speaking to create the best and most precise outcomes and even to supplant or surpass specialists' performance at this level..